Recently we asked our VP of R&D, Jon Zawistowski, PhD, to share his thoughts on the future of multiomics. He shared the following opinions:
Perspective on the Future of Multiomics
Jon Zawistowski, PhD
VP of R&D, BioSkryb Genomics
“I would posit that most of us, when looking back at our previous genomic or epigenomic datasets from 5-10 years ago, have pondered how much more transformative the same data would have been given the chance to generate it with unified, multiomic insights and the opportunity to peer into the single-cell realm of that sample!
Current methodologies have given us the chance to do just that, led mostly by advances in transcriptional profiling of individual cells in a sample that now can be also coupled with, for example, a chromatin architecture snapshot that would give clues to how both large and focal regions of the genome are poised to fire gene expression-wise. Notably, these methods show emerging beginnings of a desire to uncover the mechanistic “why” or “how” underlying the transcriptional readout that allows enumeration of cell types in a sample and assessment of physiological cell state. This trend should continue and be a requisite quest.
Exposure of a genomic variant within a subclone of cells that now seeds binding of an ectopic transcription factor or an atypical methyl-C stretch from the same individual cell that showed the gene expression aberration may now tell more of the story as to how that clone evolved and the sequence of that evolution. Such regulatory insight will be less likely to be ignored as we move to the next chapter of multiomic discovery.
Technical challenges going forward include the addition of omic tiers to the unified methodologies that accurately report those tiers with minimal perturbation to the others, and the concomitant challenge of making each of these more complete and less of partial reporting. We will need to continue the movement from a correlative linkage of uni-omic datasets (with the obvious need for computer vision) to biomarker candidates derived from the union of the datasets. A spreadsheet with multiple columns, each representing a quantitative omic value with hundreds to thousands of single cells as the rows, while enabling some aspect of hypothesis-driven inquiry, is quick visual proof of the daunting task at hand.
Finally, the economic considerations of sequencing cost and data storage will not wane as we continue to fill our proverbial spreadsheets with more cell rows and more omic FASTQ columns.
There is indeed justification to be excited about this era in which we are collectively working to innovate with new tools, trying to keep up with the amazing complexity rapidly being exposed in terms of new nucleic acid modifications, which themselves may represent new omic tiers worthy of co-inquiry along with the fundamental RNA and DNA layers.”